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31st Chinese Control Conference

作者： Yang Wen Wang Xiaofan East China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China

ISBN: (纸本)9789881563811

In this work, we consider the controlled discrete- time consensus problem in multi- agent systems, where a subset of agents take on leader roles while the remaining agents perform general consensus protocols with control inputs provided by the leaders. First, we derive necessary and sufficient conditions for the controllability under fixed and switched leaders, respectively. Further, we consider the problem of selecting a subset of followers to connect with leader for yielding fastest converging controlled consensus which can be cast as a convex optimization problem.

关键词： Distributed consensus Controllability Interconnection selection convex optimization problem Minimal convergence time

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Controllability of Discrete-time Consensus Protocol under fixed and switched leaders

Controllability of Discrete-time Consensus Protocol under fi...

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第三十一届中国控制会议

作者： YANG Wen~1,WANG Xiaofan~2 1.Key Laboratory of Advanced Control and optimization for Chemical Processes(East China University of Science and Technology), Ministry of Education,Shanghai 200237,P.R.China 2.Department of Automation,Shanghai Jiaotong University,Shanghai 200240,P.R.China

In this work,we consider the controlled discrete-time consensus problem in multi-agent systems,where a subset of agents take on leader roles while the remaining agents perform general consensus protocols with control inputs provided by the ***,we derive necessary and sufficient conditions for the controllability under fixed and switched leaders, ***,we consider the problem of selecting a subset of followers to connect with leader for yielding fastest converging controlled consensus which can be cast as a convex optimization problem.

关键词： Distributed consensus Controllability Interconnection selection convex optimization problem Minimal convergence time

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Cross-Layer Resource Allocation with Heterogeneous QoS Requirements in Cognitive Radio Networks

Cross-Layer Resource Allocation with Heterogeneous QoS Requi...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Chen, Yiyi Feng, Zhiyong Chen, Xin Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing 100876 Peoples R China

ISBN: (纸本)9781612842547

To deal with the problem that cognitive information and queuing information are not both taken into account when performing Resource Allocation (RA), we have proposed a cross-layer RA scheme in a multiuser cognitive system with Orthogonal Frequency Division Multiple Access (OFDMA). In this scheme, we assume that several crucial factors influence the RA decision, including subchannel occupancy state, subchannel link state and packets queuing state. The RA strategy is formulated as a convex optimization problem to maximize the whole system throughput with users' heterogeneous Quality of Service (QoS) requirements, considering the dynamic variations of available resources caused by the activities of licensed users. In order to solve the problem with low complexity, we present Joint Resource Allocation (JRA) algorithm involving two sub-algorithms, Minimal-Cost-Maximal-Flow Subchannel Allocation (MCMFSA) and Suboptimal Power Allocation (SPA). The innovations of the entire paper are the integrity of system model and the novelty of these algorithms, especially combining subchannel allocation with graphical theory. Simulation results indicate that the proposed scheme can achieve an excellent performance, with all QoS requirements satisfied.

关键词： Bit error rate Delay Quality of service Resource management Scheduling Sensors Throughput cognitive radio cognitive radio networks convex optimization problem convex programming cross-layer resource allocation heterogeneous QoS requirements minimal-cost-maximal-flow subchannel allocation multiuser cognitive system multiuser detection orthogonal frequency division multiple access packets queuing state quality of service resource allocation subchannel link state subchannel occupancy state suboptimal power allocation

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Min-max fair coordinated beamforming via large systems analysis

Min-max fair coordinated beamforming via large systems analy...

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IEEE International Symposium on Information Theory (ISIT)

作者： Zakhour, Randa Hanly, Stephen Univ Melbourne Dept Elect & Elect Engn Melbourne Vic 3010 Australia Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore

ISBN: (纸本)9781457705953

This paper considers base station (BS) cooperation in the form of coordinated beamforming, focusing on min-max fairness in the power usage subject to target SINR constraints. We show that the optimal beamforming strategies have an interesting nested zero-forcing structure. We then consider the asymptotic regime where the number of antennas at each BS and the number of users in each cell both grow large with their ratio tending to a finite constant. The limiting optimal beamformer structure is characterized in terms of the solution of a convex optimization problem. The dimensionality of this optimization problem is constant(1), as opposed to the problem of solving for the exactly optimal beamformer(2), and only knowledge of statistics is required to solve it. These asymptotic results provide insights into the average performance, as well as simple but efficient strategies for the finite system case. In particular, the optimal beamforming strategy from the large systems analysis only requires the base stations to have local instantaneous channel state information;the remaining parameters of the beamformer can be calculated using channel statistics which can easily be shared amongst the base stations.

关键词： Antennas Array signal processing Base stations Downlink Interference optimization SINR constraints Signal to noise ratio antennas asymptotic regime base station cooperation beam steering cellular network cellular radio channel statistics convex optimization problem convex programming large systems analysis limiting optimal beamformer structure min-max fair coordinated beamforming minimax techniques nested zero-forcing structure optimal beamforming strategy wireless channels

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On Minimizing Base Station Power Consumption

On Minimizing Base Station Power Consumption

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IEEE 74th Vehicular Technology Conference (VTC)

作者： Holtkamp, Hauke Auer, Gunther Haas, Harald DOCOMO Eurolabs D-80687 Munich Germany Univ Edinburgh Joint Res Inst Signal & Image Proc Edinburgh EH9 3JL Midlothian Scotland

ISBN: (纸本)9781424483273

We consider resource allocation over a wireless downlink where Base Station (BS) power consumption is minimized while upholding a set of required link rates. A Power and Resource Allocation Including Sleep (PRAIS) method is proposed that combines resource sharing, Power Control (PC), and Discontinuous Transmission (DTX), such that downlink power consumption is minimized. Unlike conventional approaches that aim at minimizing transmit power, in this work the BS mains supply power is chosen as the relevant metric. Based on a linear power model, which maps a certain transmit power to the necessary mains supply power, we quantify the fundamental limits of PRAIS in terms of achievable BS power savings. The fundamental limits are numerically evaluated on link level for four sets of BS power model parameters representative of envisaged future hardware developments. For BSs installed around 2014, PRAIS provides 63% to 34% energy savings over conventional resource allocation schemes, depending on the rate target per link.

关键词： Adaptation models Bandwidth IEEE 802.16 Standards Load modeling Long Term Evolution Long Term Evolution PRAIS Power demand Resource management Time division multiple access base station power consumption convex optimization problem convex programming disc

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Soft Spectrum Sensing and Power Adaptation in Multiband Cognitive Radios

Soft Spectrum Sensing and Power Adaptation in Multiband Cogn...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Mu, Hua Tugnait, Jitendra K. Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA

ISBN: (纸本)9781424492688

We consider joint optimization of spectrum sensing, channel access and power allocation in a multi-band cognitive radio network. Instead of making hard binary decisions as in traditional hypothesis testing spectrum sensing schemes, a soft spectrum sensing concept using the continuous-valued sensing test statistics is considered. The channel access decision about whether to access the channel or not is relaxed into allowing the secondary user to access channels with some probability. This joint optimization problem is aimed at maximizing the secondary users' sum throughput while keeping the interference to primary users under a specified threshold. The problem is shown to be a convex optimization problem and the Lagrangian dual method is employed to obtain the optimal solution. Two heuristic algorithms are also proposed to reduce the complexity while achieving a near optimal performance. Simulation results show that our soft sensing based algorithm significantly outperforms traditional hard decision sensing algorithms.

关键词： Cognitive radio Interference Lagrangian dual method optimization Resource management Sensors Signal to noise ratio Throughput binary decision diagrams channel access cognitive radio continuous-valued sensing test statistic convex optimization problem convex programming hard binary decisions heuristic algorithm hypothesis testing spectrum sensing scheme interference suppression joint optimization problem multiband cognitive radio network power adaptation probability probability radiofrequency interference secondary user sum throughput soft spectrum sensing

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Higher Order Positive Semidefinite Diffusion Tensor Imaging

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SIAM JOURNAL ON IMAGING SCIENCES 2010年第3期3卷 416-433页

作者： Qi, Liqun Yu, Gaohang Wu, Ed X. Hong Kong Polytech Univ Dept Appl Math Kowloon Hong Kong Peoples R China GanNan Normal Univ Sch Math & Comp Sci Jiangxi Key Lab Numer Simulat Technol Ganzhou 341000 Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China

Due to the well-known limitations of diffusion tensor imaging, high angular resolution diffusion imaging (HARDI) is used to characterize non-Gaussian diffusion processes. One approach to analyzing HARDI data is to model the apparent diffusion coefficient (ADC) with higher order diffusion tensors. The diffusivity function is positive semidefinite. In the literature, some methods have been proposed to preserve positive semidefiniteness of second order and fourth order diffusion tensors. None of them can work for arbitrarily high order diffusion tensors. In this paper, we propose a comprehensive model to approximate the ADC profile by a positive semidefinite diffusion tensor of either second or higher order. We call this the positive semidefinite diffusion tensor (PSDT) model. PSDT is a convex optimization problem with a convex quadratic objective function constrained by the nonnegativity requirement on the smallest Z-eigenvalue of the diffusivity function. The smallest Z-eigenvalue is a computable measure of the extent of positive definiteness of the diffusivity function. We also propose some other invariants for the ADC profile analysis. Experiment results show that higher order tensors could improve the estimation of anisotropic diffusion and that the PSDT model can depict the characterization of diffusion anisotropy which is consistent with known neuroanatomy.

关键词： positive semidefinite diffusion tensor apparent diffusion coefficient Z-eigenvalue convex optimization problem invariants

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Narrow and Shaped Beam Synthesis of Arbitrary Arrays via Linear Programming

Narrow and Shaped Beam Synthesis of Arbitrary Arrays via Lin...

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2010 IEEE International Symposium Antennas and Propagation/CNC-USNC/URSI Radio Science Meeting

作者： Fuchs, Benjamin Univ Rennes 1 IETR F-35014 Rennes France

ISBN: (纸本)9781424449682

Two classes of pattern synthesis problems for arbitrary arrays are addressed: narrow beam low sidelobe and shaped beam. Both problems are transformed into a linear program (LP) and can therefore be efficiently solved by many readily available algorithms. The narrow beam low sidelobe synthesis problem is rewritten as a convex optimization problem that is then easily solved to find the optimal solution. An iterative procedure is proposed to linearize and solve efficiently the shaped beam synthesis problem with simple subroutines. Numerical applications are performed to confirm the efficiency of both approaches.

关键词： antenna arrays antenna radiation patterns arbitrary arrays convex optimization problem iterative methods iterative procedure linear programming linear programming narrow beam synthesis pattern synthesis problems shaped beam antennas shaped beam synthesis

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Proportionally Fair Buffer Allocation in Optical Chip Multiprocessors

Proportionally Fair Buffer Allocation in Optical Chip Multip...

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15th CSI International Symposium on Computer Architecture and Digital Systems (CADS)

作者： Mirsadeghi, Hessam Talebi, Mohammad Sadegh Khonsari, Ahmad Ould-Khaoua, Mohamed Univ Tehran ECE Dept Tehran Iran IPM Sch Comp Sci Tehran Iran Sultan Qaboos Univ ECE Dept Muscat Oman

ISBN: (纸本)9781424462698

Advances in CMOS-compatible photonic elements have made it plausible to exploit nanophotonic communication to overcome the limitations of traditional NoCs. In this paper, we consider buffer management as a resource allocation which can be cast as a convex optimization problem. Using this framework enables us to devise a token-based optimal buffer management algorithm in optical on-chip architecture that can address fairness issues, as well. The optimal buffer allocation algorithm can be implemented by a centralized controller that is supposed to send processor elements via a simple auxiliary embedded core. Simulation results confirm that the buffer allocation algorithm manages buffer space in a fair fashion as compared to simple naive schemes.

关键词： CMOS integrated circuits CMOS-compatible photonic elements auxiliary embedded core buffer management buffer storage convex optimization problem embedded systems integrated optics microprocessor chips multiprocessing systems nanophotonic communication nanophotonics network-on-chip optical chip multiprocessors optical on-chip architecture optimal buffer management algorithm optimisation proportionally fair buffer allocation resource allocation resource allocation

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Robust Fault Diagnosis for a Class of Nonlinear Descriptor Systems

Robust Fault Diagnosis for a Class of Nonlinear Descriptor S...

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Conference on Control and Fault-Tolerant Systems (SysTol)

作者： Boulkroune, B. Zemouche, A. Univ Libre Bruxelles Dept Control Engn & Syst Anal B-1050 Brussels Belgium Nancy Univ CNRS CRAN UMR 7039 F-54400 Cosnes Et Romain France

ISBN: (纸本)9781424481545

The paper addresses the problem of designing a robust fault detection filter (RFDF) for a class of nonlinear descriptor systems whose nonlinear term are globally Lipschitz and linear term described by a linear parameter varying (LPV) form. The influence of perturbations on the residuals is minimized using the H-infinity norm while the sensitivity performance is guaranteed using the H- index. Based on the Lyapunov stability theory, the design problem is formulated as a convex optimization problem and solved via linear matrix inequality (LMI) techniques. Performances of the proposed filter are shown through the application to an activated sludge process model.

关键词： H inifinity index H inifinity norm Hâ?control Lyapunov methods Lyapunov stability theory activated sludge process model convex optimization problem convex programming fault diagnosis linear matrix inequalities linear matrix inequality linear parameter varying form nonlinear descriptor system nonlinear systems robust fault detection filter robust fault diagnosis sensitivity performance

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